High resolution synthesis using conditional GAN is not widely studied.
pix2pixHD [1]} is mainly presented to synthesize images from
semantic labels.
However, the conditional properties of GAN in the framework can be used
as an alternative approach in our case. The results are evaluated on the SUN360
test set.
Our results from the test set are shown in Figure REF . We successfully synthesize 360
panorama from partial observations. Although the baseline work performs well on semantic to
image prediction, and facial synthesis. It is shown that our results clearly outperform
pix2pixHD [1]}.
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